Predicting Indonesia Banking Financial Distress Using Ibar Z-Score Before and After Covid 19

Financial distress poses a significant threat to the stability of the banking sector, especially during periods of economic uncertainty such as the Covid-19 pandemic. This study examines financial distress in Indonesian commercial banks before and during the pandemic using the IBAR Z-Score model, which integrates CAMEL and RGEC indicators. Employing a quantitative explanatory approach with panel data from 32 banks, analyses included paired t-tests, multivariate discriminant analysis, and binary logistic regression. Findings show that 68.75% of banks were distressed pre-pandemic, decreasing to 56.25% during the pandemic, with no significant overall difference between periods. Non-Performing Loans (NPL) consistently emerged as the key distress determinant, alongside Loan to Deposit Ratio (LDR), leverage, return on equity, and Capital Adequacy Ratio (CAR) pre-pandemic, and LDR, NPL, and return on assets during the pandemic. The IBAR Z-Score demonstrated high accuracy and sensitivity to systemic shocks, confirming its utility as an early warning tool. The results offer empirical support for regulators to enhance risk-based supervision and suggest incorporating macroeconomic indicators in future predictive models, contributing to both theory and practice in banking risk management.